Advanced Subgrid-Scale Models for Particle Transport and Deposition in Gas Turbines
Abstract
The purpose of this action is to add FY23 funds in the amount of $126,134.99, for a new start Grant, GRANT#13704944.-The ingestion of environmental particulates in gas turbine engines represents one of the key challenges facing military operations in the 21st century. Airborne particles, such as sand, volcanic ash, and dust, compromise the durability, performance, and safety ofengine turbine components. Without the ability to accurately simulate dust ingestion and deposition under realistic operating conditions, the design, maintenance, and operation of gas turbine engines will be severely compromised. Large-eddy simulation (LES) is now capable of providing full-scale predictions of flow through various stages of a gas turbine engine. Yet, accurate and reliable numerical models for particle dispersion and deposition are lagging, which is the central focus of this project. Three main tasks have been identified to address this: (1) the development of advanced subgrid-scale (SGS) dispersion models based on spatially correlatedrandom walks; (2) the formulation and implementation of effectiveness factors to account for intraparticle kinetics and heat transfer in spherical/non-spherical particles; and (3) integration of these models into LES and demonstration on Navy-relevant applications. State-of-the-art SGS dispersion models treat the unresolved velocity field as a stochastic variable with random independent increments, which fail to capture particle heterogeneity that controls important phenomena such as particle dispersion, collisions, and break-up. We propose to embed two-point pairwise interactions in a manner that results in spatially correlated random increments. Stochastic inference methods will be employed to infer model coefficients from high-fidelity data. This would represent the first SGS model capable of capturing one-point fluid statistics (e.g., turbulent kinetic energy and dissipation) and two-point particle statistics (e.g., pair dispersion and clustering). In addition, a tabulated approach for fast estimation of intraparticle reactions will bedeveloped so that the internal properties of a particle can be accounted for during its lifetime within the gas turbine engine. An outcome will be an open-source library that generates lookup tables compatible with existing LES codes. The goal of developing theseadvanced models is to incorporate them into commercially available tools to be used by DoD or OEMs in engine design.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 12, 2023
- Source ID
- N000142312369
Entities
People
- Jesse Capecelatro
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy